Improving strategies in stochastic games

J. Flesch, F. Thuijsman, O.J. J Vrieze

Research output: Chapter in Book/Report/Conference proceedingChapterAcademic

Abstract

In a zero-sum limiting average stochastic game, we evaluate a\nstrategy π for the maximizing player, player 1, by the reward φ\ns(π) that π guarantees to him when starting in state s.\nA strategy π is called non-improving if\nφs(π)⩾φs(π[h]) for any state s\nand for any finite history h, where π[h] is the strategy π\nconditional on the history h; otherwise the strategy is called\nimproving. We investigate the use of improving and non-improving\nstrategies, and explore the relation between (non-)improvingness and\n(ε-) optimality. Improving strategies appear to play a very\nimportant role for obtaining ε optimality, while 0-optimal\nstrategies are always non-improving. Several examples are given to\nclarify all these issues
Original languageEnglish
Title of host publicationProceedings of the 37th IEEE Conference on Decision and Control (Cat. No.98CH36171)
Pages2674-2679
Number of pages6
DOIs
Publication statusPublished - 1998

Publication series

SeriesProceedings of the 37th IEEE Conference on Decision and Control (Cat. No.98CH36171)
Volume3

Cite this

Flesch, J., Thuijsman, F., & Vrieze, O. J. J. (1998). Improving strategies in stochastic games. In Proceedings of the 37th IEEE Conference on Decision and Control (Cat. No.98CH36171) (pp. 2674-2679). Proceedings of the 37th IEEE Conference on Decision and Control (Cat. No.98CH36171), Vol.. 3 https://doi.org/10.1109/CDC.1998.757857